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Published in:
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2013 | OriginalPaper | Chapter

1. Introduction

Author : Geoff Dougherty

Published in: Pattern Recognition and Classification

Publisher: Springer New York

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Abstract

Pattern recognition involves the recognition of objects or patterns. Classification involves sorting out particular objects into separate distinguishable categories or classes. There are wide varieties of techniques that can be used, and the advent of powerful computers has increased the demand for practical applications. Pattern recognition and classification are at the heart of most machine intelligence systems built for decision making.

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Literature
Alpaydin, E.: Introduction to Machine learning, 2nd edn. MIT Press, Cambridge (2010)MATH
Bishop, C.M.: Neural Networks for Pattern Recognition. Oxford University Press, Oxford (2006)
Duda, R.O., Hart, P.E., Stork, D.G.: Pattern Classification, 2nd edn. Wiley, New York (2001)MATH
Fu, K.S.: A step towards unification of syntactic and statistical pattern recognition. IEEE Trans. Pattern Anal. Mach. Intell. 5, 200–205 (1983)MATH
Han, J., Kamber, M.: Data Mining: Concepts and Techniques, 2nd edn. Morgan Kaufmann, San Francisco (2006)MATH
McLachlan, G.J.: Discriminant Analysis and Statistical Pattern Recognition. Wiley, New York (1992)CrossRef
Russell, S., Norvig, P.: Artificial Intelligence: A Modern Approach, 2nd edn. Prentice Hall, New York (2002)
Metadata
Title
Introduction
Author
Geoff Dougherty
Copyright Year
2013
Publisher
Springer New York
Book
Pattern Recognition and Classification

Print ISBN: 978-1-4614-5322-2

Electronic ISBN: 978-1-4614-5323-9

Copyright Year: 2013

DOI
https://doi.org/10.1007/978-1-4614-5323-9_1

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